BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Eye detection based on rank order filter
ICICS'09 Proceedings of the 7th international conference on Information, communications and signal processing
Fast eye localization based on pixel differences
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Precise eye detection using discriminating HOG features
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part I
TAROS'11 Proceedings of the 12th Annual conference on Towards autonomous robotic systems
Combining face with face-part detectors under gaussian assumption
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Hi-index | 0.00 |
Eye location is an important visual cue for face image processing such as alignment before face recognition, gaze tracking, expression analysis, etc. In this paper a novel eye detection algorithm is presented, which integrates the characteristics of single eye and eye-pair images to develop a hybrid classifier under the learning paradigm. The low dimensional features representing eye patterns yield by subspace projection are selected via a filter and a wrapper method for a simplified maximum likelihood and a SVM classifier respectively. Eye candidates determined by a cascade of the two classifiers are further verified with eye-pair template matching scores to reject false detections. The performance of this eye detector is assessed on several publicly available face databases and the experimental results demonstrate its robustness to the variations in head pose, facial expressions, partial occlusions and lighting conditions.